Anti-swing control method for grab bucket of bridge crane based on collision environment and related equipment

Abstract

The invention relates to the technical field of industrial automation control, in particular to an anti-swing control method for a grab bucket of a bridge crane based on a collision environment and related equipment. The method comprises the following steps: acquiring three-dimensional acceleration data of a grab bucket through an acceleration sensor array; recognizing a collision event for the three-dimensional acceleration data according to the collision energy to obtain collision parameters; performing swing compensation amount calculation on the collision parameter to obtain a swing compensation amount; and adjusting driving parameters of a cart or trolley moving mechanism of the bridge crane according to the swing compensation amount to obtain an anti-swing driving instruction. According to the invention, collision events can be accurately detected in real time and swing of the grab bucket can be rapidly inhibited.

Description

Technical Field

[0001] This application relates to the field of industrial automation control technology, and in particular to a method and related equipment for anti-sway control of a bridge crane grab bucket under collision conditions. Background Technology

[0002] In industrial settings such as port loading and unloading and non-ferrous smelting, crane grabs need to perform high-frequency operations. However, their operating environment is complex and variable, often leading to unexpected collisions between the grab and stacked goods, surrounding equipment, or ship hull structures. The impact force generated by such collisions can be 2-5 times the grab's own weight, triggering violent characteristic oscillations in the grab. This results in three major technical problems: first, the grab's swing angle rapidly increases within a very short time, exceeding the safe operating threshold; second, the load positioning accuracy is severely degraded, with the actual offset potentially reaching a significant proportion of the sling length; and third, the continuous oscillation significantly increases the probability of secondary collisions.

[0003] In existing technologies, there are still key technical deficiencies in addressing the above problems: In collision detection, traditional acceleration detection mechanisms use a static mode with fixed threshold judgment, which results in a significant delay in the identification of collision events. However, the main energy release process of a collision is extremely short, and this delay causes the system to miss the optimal control window. In terms of compensation models, mainstream anti-sway control algorithms are based on simplified linear sway angle models, while actual collision forces have obvious nonlinear decay characteristics, leading to a large deviation between the compensation effect and the actual situation. In terms of system architecture, existing solutions treat oscillation suppression and anti-collision functions as independent modules, lacking a coordinated control mechanism at the energy level. This fragmented design may leave behind safety hazards and may also cause new structural risks.

[0004] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0005] The main objective of this application is to propose a method and related equipment for anti-sway control of a bridge crane grab bucket under collision conditions, which can detect collision events accurately in real time and quickly suppress grab bucket sway.

[0006] To achieve the above objectives, one aspect of this application proposes a method for anti-sway control of a bridge crane grab bucket under collision conditions, the method comprising the following steps: The three-dimensional acceleration data of the grab bucket is obtained by an accelerometer array; Collision events are identified from the three-dimensional acceleration data based on the collision energy, and collision parameters are obtained. The amplitude compensation amount is calculated by performing an amplitude compensation on the collision parameters; The driving parameters of the trolley or gantry moving mechanism of the bridge crane are adjusted according to the swing amplitude compensation amount to obtain the anti-swing driving command.

[0007] In some embodiments, the method further includes the following steps: After adjustment according to the anti-sway drive command, the three-dimensional acceleration data is acquired through the acceleration sensor array; When the three-dimensional acceleration data exceeds the safety threshold, collision events continue to be identified; When the three-dimensional acceleration data is less than the safety threshold, collision event recognition stops.

[0008] In some embodiments, the center frequency of the digital filter of the acceleration sensor array is dynamically adjusted according to the sling stiffness coefficient and the mass of the grab bucket; The digital filter includes a Butterworth filter or a Chebyshev filter.

[0009] In some embodiments, the collision energy is dynamically adjusted by changes in mass and velocity; The velocity change includes the integral value of the acceleration within a time window after the moment of impact, and the time window is matched with the time scale of the impact energy.

[0010] In some embodiments, calculating the swing compensation amount from the collision parameters to obtain the swing compensation amount includes the following steps: An oscillation dynamics model is established by using a second-order nonlinear differential equation with exponential decay and sinusoidal wave terms to obtain oscillation state data; The amplitude compensation amount is obtained by linearly combining the swing state data using a proportional-derivative control algorithm.

[0011] In some embodiments, adjusting the drive parameters of the trolley or gantry moving mechanism of the bridge crane according to the swing amplitude compensation amount to obtain an anti-sway drive command includes the following steps: The actual operating speed of the moving mechanism of the bridge crane is collected to obtain a reference speed; The adjustment coefficient is obtained by processing the adjustment coefficient through a preset parameter table or an adaptive algorithm; The angle correction value of the swing compensation amount output is processed by quaternion conversion or Euler angle calculation to obtain the compensation angle; The swing angle is dynamically set based on the sling length and working environment parameters to obtain the maximum allowable swing angle; The speed correction amount is obtained by calculating the reference speed, the adjustment coefficient, the compensation angle, and the maximum allowable swing angle using a nonlinear calculation formula. The original control logic and parameters of the moving mechanism are adjusted by the speed correction amount to obtain the anti-sway drive command.

[0012] In some embodiments, the method further includes the following steps: The compensation torque is calculated when the total mechanical energy of the grab bucket is greater than the safe energy threshold. The compensation torque is dynamically adjusted based on the damping characteristics of the sling material.

[0013] In some embodiments, the method further includes the following steps: The speed of the grab and the distance between the grab and the obstacle are obtained; The dynamic safety distance threshold is obtained by multiplying the sling length according to the threshold constraint; The braking acceleration parameters are obtained by calculating the motion speed, the distance between the grab and the obstacle, and the dynamic safety distance threshold using a dynamic mathematical model of speed and braking distance. Based on the braking acceleration parameters, a smooth deceleration control of the moving mechanism is performed to obtain a secondary collision prevention control command.

[0014] To achieve the above objectives, another aspect of this application proposes a bridge crane grab bucket anti-sway control system based on a collision environment, the system comprising: An acceleration sensor array module is used to acquire three-dimensional acceleration data of the grab bucket through an acceleration sensor array; The collision detection module is used to identify collision events based on the collision energy of the three-dimensional acceleration data and obtain collision parameters. The swing compensation calculation module is used to calculate the swing compensation amount of the collision parameters to obtain the swing compensation amount; The speed control module is used to adjust the drive parameters of the trolley or gantry moving mechanism of the bridge crane according to the swing amplitude compensation amount, so as to obtain the anti-swing drive command.

[0015] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides a method and related equipment for anti-sway control of a bridge crane grab bucket under collision conditions. This scheme collects three-dimensional acceleration data of the grab bucket in real time through an acceleration sensor array, providing highly reliable raw data support for collision event identification, effectively avoiding the problem of misjudgment or omission of collision due to data acquisition deviation; furthermore, by combining collision energy with the three-dimensional acceleration data for collision event identification and collision parameter calculation of swing compensation, it can specifically capture the core influencing factors of grab bucket swing after collision, ensuring the accuracy and adaptability of swing compensation calculation, and avoiding the use of generic compensation methods. The original solution suffers from the drawback of being unable to match the complex swing state after a collision. Therefore, the driving parameters of the trolley or gantry moving mechanism of the bridge crane are adjusted based on the swing amplitude compensation to generate anti-swing drive commands. These commands can directly affect the key control links of the grab bucket swing, quickly suppressing the swing amplitude of the grab bucket after a collision. This improves the operational stability of the grab bucket during crane operation and reduces problems such as material spillage and reduced work efficiency caused by grab bucket swing. Furthermore, this solution is based on real-time data acquisition and dynamic compensation adjustment, eliminating the need for complex manual intervention. It can adapt to different collision intensities and operating conditions, enhancing the versatility and practicality of the control scheme. Attached Figure Description

[0017] Figure 1 This is a flowchart of the anti-sway control method for the grab bucket of a bridge crane under collision environment provided in the embodiments of this application; Figure 2 yes Figure 1 The flowchart of step S140 in the middle; Figure 3 This is a schematic diagram of the anti-sway control system for the grab bucket of a bridge crane under collision environment provided in an embodiment of this application; Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0021] In related technologies, crane grabs often experience violent swaying due to sudden collisions when operating in complex industrial environments. Traditional technologies employ fixed-threshold acceleration detection methods, resulting in significant delays in collision event recognition and an inability to capture the critical stage of impact energy release in a timely manner. Existing anti-sway control algorithms, based on linear swing angle models, struggle to accurately describe the nonlinear decay characteristics of collision forces, leading to discrepancies between compensation effects and actual working conditions. Furthermore, oscillation suppression and anti-collision functions operate as independent modules, lacking a coordinated control mechanism, which can easily create safety hazards.

[0022] In view of this, this application provides a method and related equipment for anti-sway control of a bridge crane grab bucket under collision conditions. This scheme reflects that the energy release from the collision is concentrated in a very short time, requiring a dynamic detection mechanism to shorten the response delay. To address the limitations of traditional linear models, a dynamic equation including nonlinear terms is proposed. Simultaneously, the isolated operation of each control step leads to ineffective suppression of energy transfer, necessitating the construction of a closed-loop collaborative control architecture. By combining high-frequency sampling, dynamic filtering, and multi-module data interaction, a real-time response mechanism is formed to rapidly suppress grab bucket sway.

[0023] Figure 1 This is an optional flowchart of a bridge crane grab bucket anti-sway control method based on a collision environment provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S110 to S140.

[0024] Step S110: Obtain three-dimensional acceleration data of the grab bucket through an acceleration sensor array; Step S120: Identify collision events based on the collision energy and three-dimensional acceleration data to obtain collision parameters; Step S130: Calculate the compensation amount for the collision parameters to obtain the swing compensation amount; Step S140: Adjust the drive parameters of the trolley or gantry moving mechanism of the bridge crane according to the swing amplitude compensation amount to obtain the anti-swing drive command.

[0025] Steps S110 to S140, as illustrated in this embodiment, involve using an array of acceleration sensors positioned at the center of gravity of the grab bucket to monitor its motion in real time and acquire its three-dimensional acceleration data. Subsequently, based on collision energy-related calculation logic, the acquired three-dimensional acceleration data undergoes high-frequency analysis and identification to determine if a collision event has occurred and to extract collision parameters. Then, using dynamic modeling methods such as second-order differential equations containing nonlinear decay terms, the collision parameters are combined to calculate the swing compensation amount, resulting in a swing compensation amount used to suppress grab bucket swaying. Finally, based on this swing compensation amount, the drive parameters of the overhead crane's main track movement mechanism and trolley lateral movement mechanism are dynamically adjusted. This adjustment generates and outputs anti-sway drive commands, thereby rapidly suppressing the grab bucket's swaying amplitude after a collision and ensuring the stability and safety of grab bucket operations.

[0026] In some embodiments, the anti-sway control method for the grab bucket of a bridge crane under collision conditions in steps S110 to S140 includes an acceleration sensor array, collision energy, swing amplitude compensation calculation, and drive parameter adjustment. The acceleration sensor array is positioned at the grab bucket's center of gravity to collect three-dimensional acceleration data in real time. More specifically, a multi-axis acceleration measurement device, implemented using a MEMS sensor array, can be positioned at the grab bucket's center of gravity to acquire the three-dimensional acceleration components of the collision impact in real time. The acceleration sensor array continuously collects grab bucket motion data at a sampling rate of not less than 500 Hz. Collision energy is used to identify collision events through high-frequency sampling. A dynamic analysis unit based on high-frequency data sampling, specifically implemented using a digital signal processor, dynamically determines collision events by analyzing the integral value of acceleration. Swing amplitude compensation calculation calculates the compensation amount based on collision parameters. A calculation unit containing nonlinear dynamic equations, specifically implemented using an embedded controller, is used to generate a compensation angle based on the collision energy parameters. Based on the dynamic equations containing nonlinear terms, the compensation angle is calculated in real time and output to the speed control. The drive parameters are adjusted based on the compensation amount. An actuator with dynamic parameter adjustment capabilities, specifically a frequency converter, is used. By changing the drive parameters of the moving mechanism, sway is suppressed, and the drive parameters of the trolley or carriage are dynamically adjusted according to the compensation angle. Each step is connected via an industrial bus to form a closed-loop control circuit. The industrial bus connection serves as a data transmission channel for real-time communication, specifically using a CAN bus or EtherCAT protocol to ensure synchronous transmission of control commands. The execution results are fed back to the sensor array via the industrial bus, forming a closed-loop control circuit.

[0027] This loop continuously monitors the oscillation state and iteratively adjusts the control input until the oscillation amplitude drops to a safe threshold. Understandably, after adjustment based on the anti-sway drive command, it acquires three-dimensional acceleration data via an acceleration sensor array; when the three-dimensional acceleration data exceeds the safe threshold, it continues to identify collision events; when the three-dimensional acceleration data falls below the safe threshold, it stops identifying collision events.

[0028] Compared with existing technologies, this application's solution reduces collision recognition time to milliseconds through high-frequency sampling and dynamic filtering techniques, overcoming the delay defects of traditional fixed threshold detection. It employs a dynamic model including a nonlinear attenuation term, making the swing amplitude compensation calculation more closely reflect the actual variation of collision force. A closed-loop control architecture is constructed through an industrial bus to achieve coordinated operation of oscillation suppression and collision avoidance, avoiding the energy superposition risk caused by isolated control.

[0029] In some embodiments, in step S110, the formula for setting the center frequency of the digital filter of the accelerometer array is: ; in, The filter center frequency (Hz) is represented by k, the sling stiffness coefficient (N / m) is represented by m, and the mass of the crane grab bucket (kg) is represented by m.

[0030] The center frequency of a digital filter refers to the frequency point where energy is concentrated within the filter's passband. It can be implemented using a Butterworth filter or a Chebyshev filter, and its center frequency is dynamically adjusted based on the sling stiffness coefficient and the grab bucket's mass. The sling stiffness coefficient refers to the sling material's resistance to deformation, which can be calculated using the material's elastic modulus and cross-sectional area. For example, when using steel cables, the stiffness coefficient can range from [specific value missing]. to The grab bucket mass refers to the total mass including the load, which can be measured in real time by a weighing sensor, for example, by dynamically updating the mass parameters during the grab bucket lifting process.

[0031] The center frequency of the digital filter is determined by the relationship between the sling stiffness coefficient and the square root of the grab bucket mass. As the grab bucket mass increases, the center frequency shifts towards lower frequencies; conversely, as the sling stiffness coefficient increases, the center frequency shifts towards higher frequencies. This dynamic matching mechanism allows the filter to accurately capture the characteristic frequency components caused by collision events, for example, when the grab bucket mass is 2000 kg and the sling stiffness coefficient is... At this point, the calculated center frequency is approximately 5Hz. With this frequency configuration, the filter can effectively remove environmental vibration noise while retaining the fundamental frequency component of the impact signal.

[0032] Compared to existing technologies, traditional methods typically use filters with a fixed center frequency, such as a uniform 10Hz, which cannot adapt to the inherent frequency shifts of the system caused by different sling materials or load variations. This solution, however, dynamically adjusts the filter characteristics through physical parameters, solving the signal detection inaccuracy problem caused by load changes or sling aging, and significantly improving the extraction accuracy of collision feature signals.

[0033] In some embodiments, the formula for calculating the collision energy in step S120 is: ; in, The value represents the collision energy (J), and m represents the mass of the crane grab bucket (kg). , Indicates instantaneous acceleration ( ), Indicates the start time (s) of the collision.

[0034] Collision energy refers to the change in kinetic energy generated during a collision, calculated by multiplying the mass by the square of the velocity change, for example, using an embedded processor for real-time numerical integration. Velocity change refers to the integral value of acceleration within a specific time window after the collision's inception, processed using the trapezoidal integral method. Preferably, the time window can be set to 0.1 seconds. The window range matches the timescale of the main energy release phase of the collision. Instantaneous acceleration refers to the real-time data collected by an accelerometer array, specifically implemented using a three-axis MEMS accelerometer, for example, by digital filtering to eliminate high-frequency noise interference.

[0035] Upon detecting a sudden acceleration change, the collision energy system immediately initiates integration, continuously collecting and accumulating acceleration data to calculate the velocity change. For example, when the grabber contacts an obstacle, the acceleration sensor array captures a pulse signal, and the collision initiation moment is locked at [time value missing]. Subsequently to The acceleration data within a second is integrated, and the result is substituted into the energy formula. This calculation process is synchronized with the physical process of collision energy release. For example, in the steel smelting scenario, the energy calculation window after the grab bucket collides with the high-temperature steel billet covers the peak impact force stage, and the energy value obtained can directly reflect the collision intensity.

[0036] Compared to existing technologies, traditional fixed-threshold detection methods only compare the acceleration amplitude at a single moment, while this solution calculates the energy value through dynamic integration, accurately capturing the temporal distribution characteristics of collision energy. For example, in port loading and unloading scenarios, when the grab bucket is in continuous contact with the cargo, existing technologies may miss detection because a single acceleration does not exceed the threshold. However, this solution accumulates the total energy of multiple acceleration pulses through integration, significantly improving the reliability of collision recognition. In some embodiments, step S130 includes the following steps: establishing an oscillation dynamics model by means of a second-order nonlinear differential equation, an exponential decay term, and a sinusoidal wave term, to obtain oscillation state data; and performing linear combination calculations on the oscillation state data by means of a proportional-derivative control algorithm to obtain the oscillation amplitude compensation amount.

[0037] Specifically, the swing amplitude compensation calculation includes two parts: the dynamic equation and the compensation angle calculation. The formula for the dynamic equation is as follows: ; in, Indicates the current grab angle. Indicates the angular velocity of the grab's swing angle. Let c represent the second-order rate of change of the grab bucket's swing angle, c represent the grab bucket's swing damping coefficient, and L represent the grab bucket's equivalent suspension length. This represents the actual acceleration data collected by the accelerometer, where m represents the mass of the crane grab bucket (kg), and p(t) represents the nonlinear term. Represents the sinusoidal wave term. , , K represents the collision energy (J), and K represents the gain coefficient related to the collision energy. This represents the exponential decay factor.

[0038] The formula for calculating the compensation angle is: ; in, , , and This indicates the range of the proportional and derivative coefficients in the proportional-derivative control algorithm. Indicates the current swing angle. This indicates the amount of amplitude compensation.

[0039] The dynamic equations refer to differential equations containing nonlinear decay terms. Specifically, they can be implemented using second-order nonlinear differential equations combined with exponential decay terms and sinusoidal fluctuation terms, used to describe the nonlinear dynamic characteristics of the grab's swing after a collision. The compensation angle calculation refers to a linear combination based on the current swing angle and its rate of change, specifically implemented using a proportional-derivative control algorithm, used to dynamically adjust the swing amplitude compensation. The parameter K is a gain coefficient related to the collision energy, specifically implemented using 80% of the collision energy value as the initial amplitude, used to reflect the influence of the collision impact intensity on the swing amplitude. and This refers to the range of proportional and differential coefficients, which can be determined by experimental calibration or system identification methods to balance response speed and system stability.

[0040] The kinetic equations are improved by introducing an exponential decay factor. Sine wave term nonlinear terms This equation can accurately characterize the decay characteristics of collision impact force over time. It incorporates actual acceleration data collected by accelerometers. By combining it with a nonlinear decay model, a swing dynamics model that more closely resembles the real physical process is established. The compensation angle is calculated by acquiring the current swing angle in real time. and its angular velocity In the proportionality coefficient and differential coefficients The compensation angle value is generated under the weighting effect of the parameter. The range of this parameter has been experimentally verified to achieve a fast response while ensuring system stability.

[0041] Compared with existing technologies, traditional linear pendulum models only consider the linear relationship between pendulum angle and angular velocity, while the dynamic equations established in this application incorporate nonlinear terms. It fully describes the attenuation process of the impact force, enabling more accurate prediction of the evolution trend of the sway after a collision. Furthermore, the compensation angle calculation uses a dynamically adjustable coefficient range instead of fixed parameters, automatically adjusting the control intensity according to actual working conditions, thus exhibiting stronger environmental adaptability compared to the static parameter settings of existing technologies.

[0042] In some embodiments, such as Figure 2 As shown, Figure 2 yes Figure 1 Flowchart of step S140 Figure 1 Step S140 includes, but is not limited to, steps S141 to S146: Step S141: Collect the actual operating speed of the moving mechanism of the bridge crane to obtain the reference speed; Step S142: Process the adjustment coefficient using a preset parameter table or an adaptive algorithm to obtain the adjustment coefficient; Step S143: Process the angle correction value of the swing compensation output through quaternion conversion or Euler angle calculation to obtain the compensation angle; Step S144: Dynamically set the swing angle based on the sling length and working environment parameters to obtain the maximum allowable swing angle; Step S145: Calculate the reference speed, adjustment coefficient, compensation angle, and maximum allowable swing angle using a nonlinear calculation formula to obtain the speed correction amount; Step S146: Adjust the original control logic and parameters of the moving mechanism by adjusting the speed correction amount to obtain the anti-sway drive command.

[0043] Specifically, in steps S141 to S146, the formula for calculating the speed correction is as follows: ; in, Indicates the speed correction amount. This represents the reference speed in the current direction of travel, and γ represents the adjustment coefficient. , Indicates the amount of swing compensation. This indicates the maximum compensation amount.

[0044] Speed ​​correction It is a dynamic adjustment of the reference speed based on the amplitude compensation result, implemented through the floating-point unit in the embedded controller, used to generate adjustment commands for the drive mechanism in real time. Reference speed This refers to the set speed of the crane's trolley or crane moving mechanism during the current operating phase. Specifically, it can use the actual speed value collected by an encoder or speed sensor as input. The adjustment coefficient γ is a proportional factor for the speed correction, which can be implemented using a preset parameter table or an adaptive algorithm. Its value range is determined through experimental calibration and is used to balance the system's response speed and stability. Compensation angle. This refers to the angle correction value output by the swing compensation calculation. It can be achieved through quaternion conversion or Euler angle calculation, and its value is related to the actual swing state of the grab after the collision. Maximum permissible swing angle. This refers to the critical angle threshold corresponding to the safe working range of the grab bucket, which can be dynamically set according to the sling length and working environment parameters.

[0045] More specifically, when the amplitude compensation calculation outputs the compensation angle Subsequently, the drive parameters are adjusted to convert the angle deviation into a speed correction using a nonlinear calculation formula. This formula processes the ratio of the angle deviation to the maximum allowable swing angle through a squared term, significantly increasing the speed correction when the swing angle approaches a critical value, thereby quickly suppressing the oscillation amplitude. The adjustment coefficient γ serves as a baseline weight in the formula, maintaining basic control strength when the swing angle is small, avoiding over-adjustment that could cause mechanism oscillation. For example, when... achieve When the swing angle reaches 70%, the coefficient of the squared term is approximately 0.49. At this point, the speed correction is adjusted to a value within the range of 0.6 to 0.9 times the base speed, forming a control strength gradient that matches the nonlinear growth of the swing angle. This calculation method can automatically adjust the control strength according to the real-time state of the swing angle, enhancing the response speed when suppressing large swings and maintaining a smooth transition when the swing angle is small.

[0046] Compared to existing technologies, traditional speed compensation methods often employ a linear product of a fixed gain coefficient and the swing angle. This can easily lead to overshoot due to insufficient control force when the swing angle approaches a critical value. This solution introduces a nonlinear calculation structure with a square term, enabling a quadratic function relationship between the speed correction and the swing angle variation. Under the same hardware conditions, this achieves more precise force-level control. For example, when the swing angle increases to 80% of the critical value, the correction increase can reach 1.6 times that of the linear calculation method, effectively shortening the adjustment time for large swing states.

[0047] In some embodiments, a compensation torque is calculated when the total mechanical energy of the grab bucket exceeds a safe energy threshold, and the compensation torque is dynamically adjusted based on the damping characteristics of the sling material.

[0048] Specifically, to monitor the energy state of the grab bucket's swing in real time, a oscillation suppression unit is also included. When the oscillation energy... At that time, calculate the compensation torque. , in, This represents the total mechanical energy generated during the grab's swinging motion. This indicates the preset safe energy threshold. This represents the reverse control quantity used to counteract residual oscillation energy. Indicates the torque generation coefficient. The compensation torque is applied to the calculation of swing amplitude compensation and the adjustment of driving parameters.

[0049] The oscillation suppression unit is a computational unit that monitors the grab bucket's swing energy state in real time. It employs an energy integration-based algorithm to determine the oscillation hazard level by continuously calculating the sum of kinetic and potential energy. This refers to the total mechanical energy during the grab's swing, which can be calculated by integrating the square of the swing angular velocity and is used to quantify the oscillation energy level. This refers to a preset safety energy threshold, which can be set based on the grab bucket's structural strength parameters, serving as the critical condition for triggering compensation control. Among these, the compensation torque... This refers to the reverse control quantity used to counteract residual oscillation energy. Specifically, it can be generated by multiplying the velocity feedback signal and the damping coefficient, and its direction of action is always opposite to the direction of the real-time oscillation angular velocity. This refers to the torque generation coefficient, which can be dynamically adjusted based on the damping characteristics of the sling material, for example, using 15 to... The numerical range is determined to ensure that the compensation torque can effectively suppress oscillations without causing overshoot.

[0050] Specifically, when the accelerometer detects that the residual oscillation energy after a collision exceeds a preset safety threshold, the oscillation suppression unit immediately initiates compensation torque calculation. By continuously collecting real-time data on the swing angular velocity, a compensation torque opposite to the swing velocity direction is generated through multiplication. This generated compensation torque is directly applied to the swing amplitude compensation calculation or drive parameter adjustment, superimposing a reverse suppression quantity on top of the original control quantity to form a closed-loop oscillation suppression mechanism. This process maintains real-time data interaction with the main control system via an industrial bus, ensuring that the timing of the compensation torque application precisely matches the system's operating state.

[0051] Compared to existing technologies, traditional solutions operate oscillation suppression as an independent step, lacking a collaborative mechanism with core steps such as amplitude compensation and speed control. The oscillation suppression unit, through the direct injection of compensating torque, organically integrates the oscillation suppression function with the main control loop, establishing a cross-module collaborative control mechanism at the energy level. This design overcomes the technical bottleneck of control command transmission delay in traditional architectures, enabling the system to respond instantly to residual oscillation energy.

[0052] In some embodiments, the method further includes the following steps: obtaining the movement speed of the grab bucket and the distance between the grab bucket and the obstacle; performing a multiple operation on the sling length according to the threshold constraint to obtain a dynamic safety distance threshold; calculating the movement speed, the distance between the grab bucket and the obstacle, and the dynamic safety distance threshold using a dynamic mathematical model of speed and braking distance to obtain braking acceleration parameters; and performing smooth deceleration control on the moving mechanism based on the braking acceleration parameters to obtain a secondary collision prevention control command.

[0053] Specifically, to prevent secondary collisions, a secondary collision prevention module is proposed, which calculates braking acceleration after a collision. The formula for calculating braking acceleration is as follows: ; in, D represents the environmental distance, k represents the safety distance factor, L represents the equivalent length of the grab bucket suspension, and v represents the real-time speed. According to Adjust the drive parameters of the trolley or carriage moving mechanism.

[0054] Braking acceleration refers to the acceleration parameter used to control the deceleration of the moving mechanism. It is calculated using the square relationship between real-time speed and environmental distance. By establishing a dynamic mathematical model between speed and braking distance, braking requirements under different working conditions can be accurately matched. The k-coefficient in the secondary collision prevention module refers to the safety distance multiplier factor, implemented using a preset threshold constraint. By using the sling length as the reference distance unit, sufficient safety margin is ensured when braking is triggered. Environmental distance D refers to the real-time distance between the grab and the obstacle, implemented using a laser rangefinder or visual recognition system. By dynamically monitoring spatial changes in the working environment, accurate input parameters are provided for braking calculations.

[0055] More specifically, after a collision, the secondary collision prevention module continuously acquires the current speed and environmental distance data of the grab bucket, and obtains a dynamic safety distance threshold by multiplying the sling length by a safety factor. When the detected environmental distance is less than 5 times the sling length, the braking acceleration is calculated in real time based on the ratio of the square of the velocity to the corrected braking distance. This acceleration parameter is transmitted to the drive parameter adjustment step, which adjusts the drive current or hydraulic pressure of the trolley or crane moving mechanism to achieve smooth deceleration control of the moving mechanism. During this process, the safety factor is set to a value of not less than 5 to ensure that a buffer distance of at least five times the sling length is maintained between the grab bucket and the obstacle when the braking process is initiated.

[0056] Compared to existing technologies, traditional collision avoidance schemes often employ fixed braking distances or single speed threshold controls, which cannot adapt to dynamic working conditions with varying combinations of sling lengths and movement speeds. This solution introduces sling length as the baseline distance unit and, by combining the mathematical relationship between the square of the velocity and the corrected distance, constructs an adaptive braking acceleration calculation model that can automatically match optimal braking parameters under different operating scenarios. Simultaneously, the safety factor effectively avoids braking lag issues caused by sensor errors or system delays.

[0057] In some embodiments, this application also proposes an anti-sway control method for the grab bucket of an unmanned bridge crane under collision conditions, comprising the following steps: acquiring three-dimensional acceleration data of the grab bucket through an acceleration sensor array at a sampling rate of not less than 500Hz; determining the occurrence of a collision based on the collision energy; solving the dynamic equation and outputting the swing compensation angle; selecting the trolley moving mechanism, the gantry moving mechanism, or both in combination as the control target according to the directional component of the compensation angle; calculating the speed correction amount of the target mechanism and generating a drive command; injecting a compensation torque when the oscillation energy exceeds a safety threshold; continuously monitoring the environmental distance and triggering braking acceleration control when the distance is less than five times the length of the sling; repeating the control loop until the actual swing angle is less than one-tenth of the maximum swing angle and the oscillation energy is less than one-fifth of the safety threshold.

[0058] Specifically, the acceleration sensor array refers to a multi-axis measuring device positioned at the grab's center of gravity, implemented using a three-axis MEMS accelerometer to capture multi-dimensional acceleration changes generated at the moment of collision. Collision energy discrimination calculates the energy threshold using integrated acceleration data, employing a short-time-window integration algorithm to identify collision events within millisecond timescales. The dynamic equation solution refers to the numerical calculation process based on a nonlinear swing angle model, specifically implemented using the fourth-order Runge-Kutta method, to accurately describe the swing amplitude decay characteristics after a collision. Directional component selection determines the control target based on the spatial decomposition results of the swing angle vector, specifically implemented using a coordinate projection algorithm, for dynamically allocating the coordinated actions of the trolley and crane mechanisms. Compensating torque injection suppresses oscillation energy through a negative feedback mechanism, specifically implemented using a torque coupler, to superimpose a damping effect in the control loop. Braking acceleration control calculates deceleration commands based on real-time distance, specifically implemented using a variable deceleration rate algorithm, to prevent secondary collision events. The dynamic iteration termination condition refers to a composite criterion based on the swing angle and energy. Specifically, it can be implemented using a dual threshold comparator to ensure that the system automatically exits the control loop after stabilizing.

[0059] In the control process following a collision with the grab bucket, acceleration data is first acquired through high-frequency sampling, for example, using a sampling frequency of 512Hz to capture the impact waveform. When the collision energy exceeds a preset threshold, the compensation calculation module is immediately activated, for example, completing the energy integral calculation within a 0.1-second time window. A nonlinear decay term is introduced during the solution of the dynamic equations, for example, embedding an exponential decay function in the differential equations to accurately simulate the decay characteristics of the actual collision force. Based on the spatial vector direction of the swing compensation angle, for example, decomposing the angle into the track direction and lateral components, the moving mechanism that needs adjustment is automatically selected. A squared proportional relationship is introduced when calculating the speed correction, for example, adjusting the reference speed by squaring the ratio of the compensation angle to the maximum safe swing angle, forming a nonlinear control response. When continuous oscillation is detected, for example, calculating the angular velocity energy using gyroscope data, and injecting a reverse compensation torque into the control loop. The secondary collision prevention module continuously monitors the distance to obstacles on the moving path, for example, using a laser rangefinder to update braking parameters in real time and dynamically adjust the deceleration curve. The termination condition of the control loop is achieved through a composite criterion, for example, stopping adjustment after simultaneously satisfying the swing angle convergence and energy dissipation conditions.

[0060] Compared to existing technologies, traditional methods using fixed thresholds for collision event detection suffer from a recognition delay of approximately 200 milliseconds, while the embodiments of this application, through dynamic energy discrimination, can complete collision confirmation within 50 milliseconds. Existing linear swing angle models generate approximately 30% phase error during compensation calculations; the nonlinear dynamic equations used in this method can control the error to within 5%. In conventional technologies, the independent operation of the anti-collision and oscillation suppression modules may lead to control command conflicts; this method eliminates approximately 80% of command conflicts through a collaborative decision-making mechanism.

[0061] In some embodiments, preferably, the system parameters are set such that the accelerometer sensor array is precisely mounted at the center of gravity of the grab bucket, and the sampling rate is set to... The center frequency of the digital filter is set as follows: The filter selected is a Butterworth bandpass filter, with a center frequency set to 6.50 Hz and a bandwidth set to [missing value]. In the threshold parameters, the safe energy threshold is set to... The maximum allowable swing angle is set to The angle is approximately 14.3°, and the oscillation suppression parameter is set to... The anti-collision parameters are set to The compensation parameters are set to , The speed correction parameter is set to In the initial state, the collision direction is set to the direction the car is moving ( (Towards), the car's base speed is set to The base speed of the large vehicle is set to .

[0062] In some embodiments, calculations relate to time processes and control. Regarding real-time sensing (…). (Moment), the accelerometer array captures Directional surge pulse. Regarding collision event recognition (… The collision initiation time is The change in velocity is The collision energy is calculated as follows: Therefore, it is determined Threshold, confirm collision. Regarding swing compensation calculation ( ), dynamic equation modeling , , Initial state acquisition , Calculation of compensation angle Regarding decisions made by sports organizations, through... The trolley mechanism is selected based on the negative X-direction. Regarding speed closed-loop control, the speed correction is calculated. The command is executed: the trolley speed is adjusted to 0.5 - 0.092 = 0.408 m / s. Regarding oscillation suppression (…). ), detect oscillation energy Calculation of compensating torque Inject swing compensation module. Regarding secondary collision prevention, monitor ambient distance. Braking acceleration calculation The large vehicle applies the brakes. Regarding the termination conditions ( Actual swing angle oscillation energy Exit the anti-sway control loop.

[0063] To achieve the above objectives, such as Figure 3 As shown, another aspect of this application proposes an anti-sway control system for a bridge crane grab bucket under collision conditions, the system comprising: Acceleration sensor array module, used to acquire three-dimensional acceleration data of the grab bucket through the acceleration sensor array; The collision detection module is used to identify collision events based on the collision energy of the three-dimensional acceleration data and obtain collision parameters. The sway compensation calculation module is used to calculate the sway compensation amount from the collision parameters to obtain the sway compensation amount; The speed control module is used to adjust the drive parameters of the trolley or gantry moving mechanism of the bridge crane according to the swing amplitude compensation amount, so as to obtain the anti-swing drive command.

[0064] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0065] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0066] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0067] Please see Figure 4 , Figure 4 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 401 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 402 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 402 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 402 and is called and executed by the processor 401 using the methods described above in the embodiments of this application. Input / output interface 403 is used to implement information input and output; The communication interface 404 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 405 transmits information between various components of the device (e.g., processor 401, memory 402, input / output interface 403, and communication interface 404); The processor 401, memory 402, input / output interface 403 and communication interface 404 are connected to each other within the device via bus 405.

[0068] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0069] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0070] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0071] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0072] It should be understood that the data used in this way can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in a sequence other than those illustrated or described herein. Furthermore, the terms “comprising” and “having”, and any variations thereof, are intended to cover a non-exclusive inclusion, for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or apparatus.

[0073] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0074] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0075] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0076] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0077] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0078] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for anti-sway control of a bridge crane grab bucket under collision conditions, characterized in that, The method includes the following steps: The three-dimensional acceleration data of the grab bucket is obtained by an accelerometer array; Collision events are identified from the three-dimensional acceleration data based on the collision energy, and collision parameters are obtained. The amplitude compensation amount is calculated by performing an amplitude compensation on the collision parameters; The driving parameters of the trolley or gantry moving mechanism of the bridge crane are adjusted according to the swing amplitude compensation amount to obtain the anti-swing driving command.

2. The method according to claim 1, characterized in that, The method further includes the following steps: After adjustment according to the anti-sway drive command, the three-dimensional acceleration data is acquired through the acceleration sensor array; When the three-dimensional acceleration data exceeds the safety threshold, collision events continue to be identified; When the three-dimensional acceleration data is less than the safety threshold, collision event recognition stops.

3. The method according to claim 1, characterized in that, The center frequency of the digital filter of the acceleration sensor array is dynamically adjusted according to the stiffness coefficient of the sling and the mass of the grab bucket; The digital filter includes a Butterworth filter or a Chebyshev filter.

4. The method according to claim 1, characterized in that, The collision energy is dynamically adjusted through changes in mass and velocity; The velocity change includes the integral value of the acceleration within a time window after the moment of impact, and the time window is matched with the time scale of the impact energy.

5. The method according to claim 1, characterized in that, The calculation of the amplitude compensation amount for the collision parameters to obtain the amplitude compensation amount includes the following steps: An oscillation dynamics model is established by using a second-order nonlinear differential equation with exponential decay and sinusoidal wave terms to obtain oscillation state data; The amplitude compensation amount is obtained by linearly combining the swing state data using a proportional-derivative control algorithm.

6. The method according to claim 1, characterized in that, The step of adjusting the drive parameters of the trolley or gantry moving mechanism of the bridge crane according to the swing amplitude compensation amount to obtain the anti-sway drive command includes the following steps: The actual operating speed of the moving mechanism of the bridge crane is collected to obtain a reference speed; The adjustment coefficient is obtained by processing the adjustment coefficient through a preset parameter table or an adaptive algorithm; The angle correction value of the swing compensation amount output is processed by quaternion conversion or Euler angle calculation to obtain the compensation angle; The swing angle is dynamically set based on the sling length and working environment parameters to obtain the maximum allowable swing angle; The speed correction amount is obtained by calculating the reference speed, the adjustment coefficient, the compensation angle, and the maximum allowable swing angle using a nonlinear calculation formula. The original control logic and parameters of the moving mechanism are adjusted by the speed correction amount to obtain the anti-sway drive command.

7. The method according to claim 1, characterized in that, The method further includes the following steps: The compensation torque is calculated when the total mechanical energy of the grab bucket is greater than the safe energy threshold. The compensation torque is dynamically adjusted based on the damping characteristics of the sling material.

8. The method according to claim 1, characterized in that, The method further includes the following steps: The speed of the grab and the distance between the grab and the obstacle are obtained; The dynamic safety distance threshold is obtained by multiplying the sling length according to the threshold constraint; The braking acceleration parameters are obtained by calculating the motion speed, the distance between the grab and the obstacle, and the dynamic safety distance threshold using a dynamic mathematical model of speed and braking distance. Based on the braking acceleration parameters, a smooth deceleration control of the moving mechanism is performed to obtain a secondary collision prevention control command.

9. A bridge crane grab bucket anti-sway control system based on collision environment, characterized in that, The system includes: An acceleration sensor array module is used to acquire three-dimensional acceleration data of the grab bucket through an acceleration sensor array; The collision detection module is used to identify collision events based on the collision energy of the three-dimensional acceleration data and obtain collision parameters. The swing compensation calculation module is used to calculate the swing compensation amount of the collision parameters to obtain the swing compensation amount; The speed control module is used to adjust the drive parameters of the trolley or gantry moving mechanism of the bridge crane according to the swing amplitude compensation amount, so as to obtain the anti-swing drive command.

10. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 8.

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